家电科技 ›› 2024, Vol. 0 ›› Issue (zk): 27-32.doi: 10.19784/j.cnki.issn1672-0172.2024.99.006

• 第一部分 优秀论文 • 上一篇    下一篇

面向最小实验数据需求的压缩机模型优选

翁晓敏1, 王龙炎2, 丁国良2   

  1. 1.广东美的暖通设备有限公司 广东佛山 528311;
    2.上海交通大学机械与动力工程学院 上海 200240
  • 出版日期:2024-12-10 发布日期:2024-12-31
  • 通讯作者: 丁国良,E-mail:glding@sjtu.edu.cn。
  • 作者简介:翁晓敏,硕士学位。研究方向:制冷系统建模仿真。地址:佛山市顺德区美的全球创新中心6栋2楼。E-mail: wengxm1@midea.com。

Optimal selection of compressor models for minimum experimental data requirements

WENG Xiaomin1, WANG Longyan2, DING Guoliang2   

  1. 1. Guangdong Midea Heating & Ventilating Equipment Co., Ltd., Foshan 528311;
    2. School of Mechanical Engineering, Shanghai Jiao Tong University Shanghai 200240
  • Online:2024-12-10 Published:2024-12-31

摘要: 制冷系统仿真用的压缩机模型,除了提升精度外,还要求用于校正模型所需要用到的实验样本越少越好。基于实验测试数据对不同的模型进行对比,从精度相对较好的模型中选出实验数据需求量最小的压缩机模型。结果表明,对于压缩机的流量,使用多变指数的倒数对压比项进行修正,并考虑吸气过程的压力损失进行表征;对于压缩机的功率,使用高、低压和高低压的交叉项进行表征,可以同时满足精度高且数据需求量小的要求。仅需5组实验数据即可准确拟合压缩机模型中的待定系数,模型对压缩机的流量和功率预测的平均误差分别在1.5%和2%以内。

关键词: 压缩机, 压缩机模型, 十系数模型, 数据需求量

Abstract: In addition to improving accuracy, the compressor model used in refrigeration system simulation also requires as few experimental samples as possible for model correction. Based on experimental test data, different models are compared. And the compressor model with the smallest experimental data requirement is selected from the models with relatively good accuracy. The results show that for mass flow rate, the reciprocal of the polytropic index is used to correct the pressure ratio term, and the pressure loss of the suction process is considered for characterisation; for input power, high and low pressure and high and low pressure cross terms are used for characterisation, which can meet the requirements of high accuracy and small data requirement at the same time. Only 5 sets of experimental data are required to accurately fit the undetermined coefficients in the compressor model, and the average errors of the model prediction of mass flow rate and input power are within 1.5% and 2%, respectively.

Key words: Compressor, Compressor model, Ten-coefficient model, Data requirement

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